马来语卡达山都逊语计算机辅助资源不足语言翻译的应用

Mohd Shamrie Sainin, Minah Sintian, Suraya Alias, Asni Tahir
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引用次数: 0

摘要

使用机器翻译(MT)的计算机辅助语言翻译是由计算机(机器)执行的将一种自然语言翻译成另一种自然语言的应用程序。有许多在线语言翻译工具,但到目前为止,没有一个提供资源不足的卡达赞都孙语的文本翻译序列。虽然有基于网络和移动应用程序的Kadazandusun词典,但这些系统只能翻译一个单词。因此,本文旨在探讨马来语对卡达山都逊语的初步翻译。选择基于直接机器翻译(DMT)的字典对齐的基本词对词翻译,开始对翻译领域的探索,其中DMT是最早依赖于词对词方法(序列对序列模型)的翻译方法之一。本文旨在探讨资源不足的语言和从马来语到卡达山都孙语或反之亦然的翻译任务。本文介绍了该系统的应用、过程和结果,根据卡达赞杜孙语基本词序(动词-主-宾)及其翻译质量,使用BLEU(双语评价Understudy)评分。翻译过程涉及几个阶段,包括数据收集(词对翻译)、预处理、文本选择、翻译程序和性能评估。初步的语言翻译方法被证明能够产生高达0.5的BLEU分数,这表明翻译是可读的,但需要后期编辑以更好地理解。这些发现对于资源不足的语言翻译的质量具有重要意义,并作为其他机器翻译方法(如统计或基于深度学习的翻译)的起点。
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The Application of Computer-Aided Under-Resourced Language Translation for Malay into Kadazandusun
A computer-aided language translation using a Machine translation (MT) is an application performed by computers (machines) that translates one natural language to another. There are many online language translation tools, but thus far none offers a sequence of text translations for the under-resourced Kadazandusun language. Although there are web-based and mobile applications of Kadazandusun dictionaries available, the systems do not translate more than one word. Hence, this paper aims to present the discussion of the preliminary translation of Malay to Kadazandusun. The basic word-to-word with dictionary alignment translation based on Direct Machine Translation (DMT) is selected to begin the exploration of the translation domain where DMT is one of the earliest translation methods which relies on the word-to-word approach (sequence-to-sequence model). This paper aims to investigate the under-resourced language and the task of translating from the Malay language to the Kadazandusun language or vice versa. This paper presents the application and the process as well as the results of the system according to the basic Kadazandusun word arrangement (Verb-Subject-Object) and its translation quality using the Bilingual Evaluation Understudy (BLEU) score. Several phases are involved during the process, including data collection (word pair translation), preprocessing, text selection, translation procedures, and performance evaluation. The preliminary language translation approach is proven to be capable of producing up to 0.5 BLEU scores which indicate that the translation is readable, however, requires post-editing for better comprehension. The findings are significant for the quality of the under-resourced language translation and as a starting point for other machine translation methodologies such as statistical or deep learning-based translation.
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来源期刊
Annals of Emerging Technologies in Computing
Annals of Emerging Technologies in Computing Computer Science-Computer Science (all)
CiteScore
3.50
自引率
0.00%
发文量
26
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